The evenness or equality with which income is dealt out among members of a society is reflected in the income distribution. If everyone earned exactly the same amount of money, then the income distribution would be perfectly equal. If no one earned any money except for one person, who earned all of the money, then the income distribution would be perfectly unequal. Usually, however, a society's income distribution falls somewhere in the middle between equal and unequal. How do we measure the degree of equality or inequality?  

The Quintile Method

Economists often measure income equality by measuring how much income is earned by different segments of the population. Very often, economists break down all workers into five segments in terms of how much money they make: the top 20%, the second 20%, the third 20%, the fourth 20%, and the bottom 20%. With the right data, we can create a chart detailing how much income each segment earns out of the total amount of income for all workers. 

Let's say that the average incomes for five segments in a society are $10,000, $24,000, $50,000, $80,000, and $110,000. To look at income distribution, we need to see what percentage of total income each segment makes, rather than the actual amount of money each makes. Since each of the segments contains the same number of people, we don't need to worry about weighting the average incomes and can do a straightforward part-over-whole calculation of each segment's earnings. 

For total income we will use the sum of the five average incomes: \($10,000+$24,000+$50,000+$80,000+$110,000 = $274,000\)

Next we find the percentage of total income that each segment of the population earns, by dividing that segment’s income by the total income: 

Segment 1: \($10,000/$274,000 = 0.036 = 3.6\%\)

Segment 2: \($24,000/$274,000 = 0.088 = 8.8\%\)

Segment 3: \($50,000/$274,000 = 0.182 = 18.2\%\)

Segment 4: \($80,000/$274,000 = 0.292 = 29.2\%\)

Segment 5: \($110,000/$274,000 = 0.401 = 40.1\%\)

(Note: The total cumulative percentage here is 99.9% due to rounding. It should be equal to 100%, since it represents the total income earned by all workers.)

What these figures indicate is that the bottom fifth of the population gets less than 4% of the total income, while the top fifth of the population gets over 40% of the total income. This is a high degree of income inequality. 

Lorenz Curves and Gini Coefficients

Economists also look at cumulative figures for income distribution. To find the cumulative figures, simply add the percentages together at each level, giving the amount of income earned by all people at or below a certain level. In our example, the results are as follows: 

Segment 1 cumulative percentage: \(3.6\%\)

Segment 2 cumulative percentage: \(3.6\%+ 8.8\% = 12.4\%\)

Segment 3 cumulative percentage: \(12.4\% + 18.2\% = 30.6\%\)

Segment 4 cumulative percentage: \(30.6\%+29.2\%=59.8\%\)

Segment 5 cumulative percentage: \(59.8\%+40.1\%=99.9\%\)

(Note: Again, the total cumulative percentage here is 99.9% due to rounding, but should equal 100%.)

If we plot these values in a graph with quintiles on the horizontal axis and cumulative percentages on the vertical axis, we can compare the resulting curve to a perfectly equal income distribution, which would be a straight-line graph: 

The calculation of the Gini coefficient, using a graph with percent of population on the horizontal axis and percent of income on the vertical axis. A concave up, everywhere increasing curve runs from the origin to the point 100 percent, 100 percent. This is the Lorenz curve. The area below the curve is labeled B. A straight line also runs from the origin to the point 100 percent, 100 percent. The area below this line and above the Lorenz curve is labeled A. 

This type of graph, showing income distribution among population segments, is called a Lorenz curve. Using the Lorenz curve, we can also generate a numerical representation of income inequality called the Gini coefficient. The Gini coefficient, which ranges between 0 and 1, is equal to the area between the actual and equal-distribution curves divided by the total area under the equal-distribution curve. In the figure, the Gini coefficient is equal to the area of region \(A\) divided by the area of region \(A+B\). The greater the Gini coefficient, the greater the degree of income inequality. A perfectly equal income distribution will have a Gini coefficient of 0, while a perfectly unequal distribution will have a Gini coefficient of 1. 

Income mobility

Another factor to consider when studying the degree of inequality in a society is the amount of income mobility. Income mobility refers to the ease with which workers can move up and down in the hierarchy of earning power. If the rich always stay rich and the poor always stay poor, then an unequal income distribution is a permanent and serious problem. If workers easily shift from middle class to upper class or from lower class to middle class, however, then the degree of inequality becomes less serious, since the inequality is fluid and temporary (on an individual basis).